Genes predict if medication can help you quit smoking
The same gene variations that make it difficult to stop smoking also increase the likelihood that heavy smokers will respond to nicotine-replacement therapy and drugs that thwart cravings, a new study shows.
The research, led by investigators at Washington University School of Medicine in St. Louis, will appear online May 30 in the American Journal of Psychiatry.
The study suggests it may one day be possible to predict which patients are most likely to benefit from drug treatments for nicotine addiction.
“Smokers whose genetic makeup puts them at the greatest risk for heavy smoking, nicotine addiction and problems kicking the habit also appear to be the same people who respond most robustly to pharmacologic therapy for smoking cessation,” says senior investigator Laura Jean Bierut, MD, professor of psychiatry. “Our research suggests that a person’s genetic makeup can help us better predict who is most likely to respond to drug therapy so we can make sure those individuals are treated with medication in addition to counseling or other interventions.”
For the new study, the researchers analyzed data from more than 5,000 smokers who participated in community-based studies and more than 1,000 smokers in a clinical treatment study. The scientists focused on the relationship between their ability to quit smoking successfully and genetic variations that have been associated with risk for heavy smoking and nicotine dependence.
“People with the high-risk genetic markers smoked an average of two years longer than those without these high-risk genes, and they were less likely to quit smoking without medication,” says first author Li-Shiun Chen, MD, assistant professor of psychiatry at Washington University. “The same gene variants can predict a person’s response to smoking-cessation medication, and those with the high-risk genes are more likely to respond to the medication.”
In the clinical treatment trial, individuals with the high-risk variants were three times more likely to respond to drug therapy, such as nicotine gum, nicotine patches, the antidepressant buproprion and other drugs used to help people quit.
Tobacco use is the leading cause of preventable illness and death in the United States and a major public health problem worldwide. Cigarette smoking contributes to the deaths of an estimated 443,000 Americans each year. Although lung cancer is the leading cause of smoking-related cancer death among both men and women, tobacco also contributes to other lung problems, many other cancers and heart attacks.
Bierut and Chen say that the gene variations they studied are not the only ones involved in whether a person smokes, becomes addicted to nicotine or has difficulty quitting. But they contend that because the same genes can predict both heavy smoking and enhanced response to drug treatment, the genetic variants are important to the addiction puzzle.
“It’s almost like we have a ‘corner piece’ here,” Bierut says. “It’s a key piece of the puzzle, and now we can build on it. Clearly these genes aren’t the entire story — other genes play a role, and environmental factors also are important. But we’ve identified a group that’s responding to pharmacologic treatment and a group that’s not responding, and that’s a key step in improving, and eventually tailoring, treatments to help people quit smoking.”
Since people without the risky genetic variants aren’t as likely to respond to drugs, Bierut says they should get counseling or other non-drug therapies.
“This is an actionable genetic finding,” Chen says. “Scientific journals publish genetic findings every day, but this one is actionable because treatment could be based on a person’s genetic makeup. I think this study is moving us closer to personalized medicine, which is where we want to go.”
And Bierut says that although earlier studies suggested the genes had only a modest influence on smoking and addiction, the new clinical findings indicate the genetic variations are having a big effect on treatment response.
“These variants make a very modest contribution to the development of nicotine addiction, but they have a much greater effect on the response to treatment. That’s a huge finding,” she says.
About this psychiatry research article
Chen LS, Baker TB, Piper ME, Breslau N, Cannon DS, Doheny KF, Gogarten SM, Johnson EO, Saccone NL, Wang JC, Weiss RB, Goate AM, Bierut LJ. Interplay of genetic risk factors (CHRNA5-CHRNA3-CHRNB4) and cessation treatments in smoking cessation success. American Journal of Psychiatry, published online May 30, 2012; doi:10.1176/appi.ajp.2012.11101545.
Bierut, Goate and Wang are listed as inventors on issued U.S. Patent 8,080,371, “Markers for Addiction” covering the use of certain SNPs in determining the diagnosis, prognosis and treatment of addiction.
Funding for this research comes from the National Cancer Institute, the National Institute on Drug Abuse, the National Human Genome Research Institute, the National Heart, Lung, and Blood Institute and the National Center for Research Resources of the National Institutes of Health (NIH). NIH grant numbers P01 CA089392, P50 CA84724, K05 CA139871, P50 DA19706, R01 DA026911, K02 DA021237, K08 DA030398, U01 HG004422, KL2 RR024994, U01 HG004438, HHSN268200782096C (contract), U01 HG004446, N01 HC55015 (contract), N01 HC55016 (contract), N01 HC55018 (contract), N01 HC-55019 (contract), N01 HC55020 (contract), N01 HC55021 (contract), N01 HC55022 (contract), R01 HL087641, R01 HL59367, R01 HL086694, U01 HG004402, HHSN268200625226C (contract) and UL1 RR025005.
Contact: Jim Dryden – Washington University in St. Louis
Source: Washington University in St. Louis press release
Image Source: Psychology smoking image adapted from Wikimedia Commons user Kain Road Cul de Sac. Licensed under the Creative Commons Attribution 2.0 Generic.
Original Research: Abstract for “Interplay of Genetic Risk Factors (CHRNA5-CHRNA3-CHRNB4) and Cessation Treatments in Smoking Cessation Success” by Li-Shiun Chen, M.D., M.P.H., Sc.D.; Timothy B. Baker, Ph.D.; Megan E. Piper, Ph.D.; Naomi Breslau, Ph.D.; Dale S. Cannon, Ph.D.; Kimberly F. Doheny, Ph.D.; Stephanie M. Gogarten, Ph.D.; Eric O. Johnson, Ph.D.; Nancy L. Saccone, Ph.D.; Jen C. Wang, Ph.D.; Robert B. Weiss, Ph.D.; Alison M. Goate, D.Phil.; Laura Jean Bierut, M.D. Published online at American Journal of Psychiatry 2012. doi:10.1176/appi.ajp.2012.11101545